Papers

8

Total Citations

208

H-Index

3

About

Lepeng Song is a pioneering researcher at the intersection of agricultural robotics and intelligent sensing systems. His work primarily focuses on developing autonomous robotic solutions for precision agriculture, with key contributions in multi-sensor fusion, trajectory tracking control, and thermal imaging applications for livestock management. Song’s most impactful work, the comprehensive review "Infrared and Visible Image Fusion Technology and Application: A Review" (2023), has garnered 165 citations, establishing a foundational resource for researchers working on robust imaging systems that overcome the limitations of single-sensor approaches. He has made significant strides in agricultural automation, designing an autonomous inspection robot for detecting dead laying hens in caged layer houses (2024) and developing advanced control algorithms for lawn mowing robots using sliding mode control with extended state observers (2022). His innovative use of thermal infrared imaging for pig ear detection, introducing the TIRPigEar dataset, demonstrates his commitment to non-invasive animal monitoring. Song’s recent work on orchard robot path planning, combining improved ant colony algorithms with dynamic window approaches (2025), continues to push boundaries in autonomous navigation for complex agricultural environments.

Research Focus

Key Achievements

3
H-Index
8
Papers
208
Total Citations
26
Avg Citations/Paper
🏆 Most Cited Paper
Infrared and Visible Image Fusion Technology and Application: A Review
165 citations · 2023
📈 Most Prolific Year: 2024 (2 Papers)
🤝 Key Collaborators: 24
🏛 Institutions: Chongqing University of Science and Technology, Agricultural Research Service

Top Papers

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Key Collaborators

Contact & Links

Available for collaboration
Content generated · 13 days ago